JP2016509317A - Predictive storage service - Google Patents

Abstract

The predictive storage application selectively determines files from a computing system that should be sent to a predictive storage service that makes the file available to another computing system. The predictive storage application can receive an event indicating the use of a file. The predictive storage application can determine that the file has sufficient importance and send it to the predictive storage service. Other aspects of the disclosure are set forth in the detailed description, drawings, and claims.

Description

  Documents are an important part of the workflow, and they perform various functions such as tracking, reporting, education and payment functions. For example, children and teachers are working on handouts and reports. In another example, a mechanic tracks parts, labor, and completion during repair. Using these documents allows the workflow to continue because the state of the workflow can be reflected in the document.

  As documents and content are built, people increasingly consider and edit content on various devices. For example, executives email themselves to the latest spreadsheet with key business indicators so they can review the spreadsheet on their smartphone. In another example, the attorney's secretary places the file on a USB drive and gives the attorney so that it can be viewed on a laptop while traveling. In yet another example, an artist saves assets and work in progress in a pre-confirmed folder that synchronizes changes to a remote server.

Various embodiments according to the invention will now be described with reference to the drawings, in which:
FIG. 6 illustrates an example that helps explain a predictive storage service according to at least one embodiment. FIG. 5 illustrates an example that helps explain a predictive storage service using a file structure according to at least one embodiment. FIG. 6 illustrates an example that helps illustrate a process that can be used to synchronize files to a predictive storage service according to at least one embodiment. FIG. 6 illustrates an example that helps illustrate a process used to determine files to select in a predictive storage service according to at least one embodiment. FIG. 6 illustrates an example that helps illustrate a process used to determine files to select in a predictive storage service according to at least one embodiment. FIG. 6 illustrates an example that helps illustrate a process that can be used to synchronize files with a predictive storage service according to at least one embodiment. FIG. 6 illustrates an example that helps illustrate a process that may be used to store a file in a predictive storage service according to at least one embodiment. FIG. 5 is an illustration useful for explaining a data center organization according to at least one embodiment. An environment in which various embodiments are implemented is described.

  In the following description, various embodiments will be described. For purposes of explanation, specific configurations and details are set forth in order to provide a thorough understanding of the embodiments. However, it will be apparent to one skilled in the art that the embodiments may be practiced without the specific details. In other instances, well-known features may be omitted or simplified in order not to obscure the described embodiments.

  The techniques described and recommended include selectively determining which files to send to the storage service from a file structure that creates files available for use elsewhere. For example, a user may register a computing system such as a desktop computer or mobile device with an account. A user can cause a desktop computer and / or mobile device to install a predictive storage application that monitors activity on these registered computing systems.

  As an illustrative example, the predictive storage application may determine that a user has downloaded and opened a PDF file on a laptop computer. While the PDF file is open on the laptop computer, the predictive storage application can receive notification that the user has also opened the word processing document. The predictive storage application may then receive an event where the window focus shifts multiple times between the PDF and the word processing document on the laptop computer. Saving an event for a word processing document is of sufficient importance based at least in part on the fact that the user interacts with the file and the PDF and the word processing document are sent to the predictive storage service. The predictive storage application may determine that the word processing document has. Once in the predictive storage service, PDFs and word processing documents can persist or be sent to registered mobile phones. Any further changes made to either the PDF or word processing document on the laptop computer can also be synchronized to the predictive storage application and / or the mobile phone. When the user shuts down the laptop computer, the user can review the PDF on the mobile phone and continue editing the word processing document.

  The predictive storage application can monitor the file structure of the computing system. In one embodiment, the virtual desktop provided as a service includes a predictive storage application that monitors the file system. The file system may be based on volumes, object storage devices or other data containers. The monitoring information can be determined via events, notifications, polling or other push or pull based information or combinations thereof. The monitoring information can be received from other sources of monitoring information for applications, operating systems, hypervisors, plug-ins and / or combinations thereof. For example, an application can register with the operating system to receive notifications when files from a set of file types are opened, closed, created, modified, and / or destroyed. In another embodiment, the application can include the plug-in in the word processor, notifying the application when the file is opened, closed, saved, auto-saved, and / or saved offer is rejected. In yet another embodiment, the application periodically scans the file structure in the volume for recent changes to modified, open, created or other dates and information stored in the file structure. be able to. During scanning, the metadata of other files is printed by author, title, subject, tag, category, last saved user name, revision number, version number, application name, creation date, last saved date, last printed Date, last accessed date, date brought in, date acquired, copyright, dimensions, width, height, resolution, compression, camera, ISO speed, serial number, file structure path, page, word, character, Things like lines, paragraphs and / or sizes can be collected.

  The predictive storage application may determine which files to upload based at least in part on a quantified data inference algorithm. The algorithm can use a measure of importance, such as a rule of thumb, to determine the importance of uploading the file. By determining which files are important to upload, upload bandwidth and storage resources can be used more efficiently. For example, instead of uploading the entire file structure (or part of it), only the identified file is uploaded. This selective upload allows the predictive storage application to focus on synchronizing files of measured importance instead of forcing the user to save everything in the folder. This selective upload can also avoid uploading documents that may not be useful as a temporary or administrative file. Using the structure of the file within the file structure and / or information gathered about the file, the predictive storage application can determine which files to upload to the storage service based on the importance measure. For example, the importance index may be the number of times the user interacted with the file over time. The algorithm can be used to evaluate files according to importance indicators. The application can be configured to upload the top X percent of the file (where X is a configurable variable) to the service. In another configuration, the algorithm can rank the files and weight the rating of each file to adjust its overall rating. To determine the importance index that calculates the file's importance rating, the monitoring program can close the document type, file opening recency, the length of time the file was open, and when it was opened, for example. Changes in the overall file size, keywords and author information can be used until Files with the word processing type recently opened by authors that match machine logins can receive a higher importance rating. Upload schedules can also be prioritized according to the determined importance. In another example, the determined importance may be based at least in part on an application installed on the computing system. In one embodiment, a file may be determined to have a relationship with an installed application if an icon is associated with the file type of the file. For example, a “txt” file extension may have an association with an icon due to a word processing program that provides icons for all “txt” extension files. If the computing system has a word processor installed but does not have a spreadsheet, the files related to word processing will get a high rating, but the files related to the spreadsheet will be important The rating may be reduced.

  In one embodiment, the predictive storage service stores the file. The predictive storage service can receive files from a registered computing system, such as via communication with a predictive storage application on the registered computing system. The registered computing system may be a computing system associated with a customer account. In one embodiment, the client may register with the predictive storage service to receive files associated with the customer's account. For example, a customer can install a software client on a computing system. As part of the installation, the software client may request account information such as a username and password or key and register it with the predictive storage service. The predictive storage service can then provide an identifier or key to the software client that can be used to identify the software client in future connections. In another embodiment, the predictive storage service can be coordinated with a virtual desktop service. Virtual desktop service customers can create accounts with service providers. A virtual machine that includes an operating system with a software client can be provisioned by a virtual desktop service and a graphical user interface created by the operating system can be streamed to a client device. In this configuration, the software client can pre-provision account information to allow communication with the predictive storage service.

  The predictive storage service may then store the file. In one embodiment, the predictive storage service may provide other services related to the file. For example, the storage service may index the file so that a search can be performed to find the file and / or information within the file. A search may return a snippet from a file with content both before and after the searched information. In another embodiment, the predictive storage service receives and stores the encrypted file. Because the file is encrypted by the sending device, the predictive storage service can store the file and relay it to other registered computing systems that can decrypt the file. The risk of intrusion can be mitigated by the fact that storage services do not have access to data and only store encrypted payloads. In another embodiment, a hybrid approach is taken when an encrypted payload is stored, but the predictive storage service also has an encryption key. In another hybrid approach, the encrypted payload is stored with an index in the encrypted payload.

  In some embodiments, the stored file may be deleted from the predictive file service. Deletion may be based on current determined importance, usage, space and / or time. For example, the file may be excluded in a time-out model. If the saved file has not been accessed on the registered computing system for a certain amount of time, the file may be deleted from the predictive storage service. In another embodiment, the file may be driven to a least recently used (LRU) model. If the predictive storage service determines that a file must be deleted from storage, the predictive storage service can select the file to delete that has been the longest time since it was accessed. In other embodiments, the predictive storage service may receive and request importance ratings and / or importance indicators from registered devices for files stored in the predictive storage service. . These ratings have a rating of importance and if there is something like a file that does not pass the threshold, or a low outlier file from a statistical analysis of the importance rating distribution, which file should be stored You can decide whether to delete from the service.

  In some embodiments, the predictive storage service relays files to registered devices. The predictive storage service may act as an intermediary for distributing files. In one embodiment, the predictive storage service can temporarily store the file while the registered device receives the file. In one embodiment, the predictive storage service facilitates peer connections so that devices send files to each other and the predictive storage service does not store files.

  Turning now to FIG. 1, an illustrative example of a predictive storage service 100 in accordance with at least one embodiment is shown. In the illustrated embodiment, the file 102 accessed on the first computing system is transferred to the second computing system to be facilitated by the predictive storage service 100 for further access by the user. The predictive storage service 100 can use the importance index to determine which files to transfer. For example, the user accesses a file 102, such as a word processing file, accessed on the desktop computer 104. The predictive storage application resident on the desktop computer 104 determines that the accessed file 102 is important to the user because recent access to the file can be an indicator of importance. In some embodiments, the importance is calculated from a series of importance indicators calculated by an algorithm or heuristic using several measurements. The measurements may include monitoring information and / or file metadata as described above. Since the file 102 has an importance determined high enough, the predictive storage service 110 may be contacted. In some embodiments, the file may be sent to the predictive storage service 110 via the Internet 108. Using one or more servers 112, the predictive storage service 110 can store the file 102. In some embodiments, the predictive storage service 110 may then attempt to contact the mobile device 106 and send the file 102 to the mobile device, such as via push notifications or other push techniques. In other embodiments, the mobile device 106 can contact the predictive storage service 110 and may request an update from the predictive storage service 110 to receive the file 102. This request for updates from the mobile device 106 is due to launching a predictive storage application on the mobile device 106, periodic polling requests from the mobile device 106, events on the mobile device 106, or other pull techniques. It is.

  In other embodiments, the predictive storage service 110 may prepare to send the file 102 directly to the mobile device 106. In one embodiment, the registered device may remain in contact with the predictive storage service 110. For example, when it is determined that an important file should be shared with other computer systems, the desktop system 104 contacts the predictive storage service 110 to provide contact information for other computing systems such as the mobile device 106. Can be taken out. Depending on the configuration, the desktop system 104 can connect directly to the mobile device 106, the mobile device 106 can connect directly to the desktop system 104, and the predictive storage service 110 can connect the desktop system 104 to the mobile device 106. A proxy or other connection between them may be opened. Using the connection, the desktop system 104 can send the file 102 to the mobile device 106.

  The desktop and / or mobile device 106 can register with the predictive storage service 110. In one embodiment, the customer creates an account with the predictive storage service 110. The customer can then install the application on each of the computing systems, such as desktop computer 104 and mobile device 106. The application can register the computing system with the predictive storage service 110 and associate the customer's account with the computing system.

  In another embodiment, the predictive storage service 110 may operate in conjunction with the virtual desktop service 114. For example, a service provider operating the virtual desktop service 114 can start a virtual machine with an operating system for the user. The user interface 118 for the operating system can be streamed to a computing system operated by the user. The virtual desktop service 114 may comprise one or more physical machines 116 that physically execute one or more virtual machines that execute programs on the virtual machine and stream a user interface 118 for the operating system to the client. Provided by the machine. Input from the user interface 118 can be streamed to the desktop service 114. For example, the virtual machine can export the operating system graphical user interface to a remote laptop and receive keyboard and mouse input from the remote laptop. An example of the configuration of the virtual machine in the data center can be seen in FIG. The virtual desktop service 114 can communicate with the predictive storage service 110 over a network or the Internet to create a file 102 that can be used in the user interface 118. In one embodiment, the virtual desktop environment may execute the program on a virtual machine that accesses and / or modifies the file 102. The display of the virtual desktop service 114 may be exported for display on the client computing resource, while processing of the file 102 and execution of the desktop environment program occurs within the desktop service 114. Input such as a mouse, touch and / or keyboard may be communicated from the user interface 118 to the virtual desktop service 114.

  In some embodiments, the predictive storage service 110 provides access to the file 102 via a web interface. In one embodiment, the web interface includes a download function for downloading important files. In another embodiment, the web interface includes an editing function for editing a file via the web interface. For example, a word processing document can be edited via a web interface resulting from a word processing web application available via the web interface. Other file types and applications can also be made available, such as a spreadsheet web application for spreadsheet file types or an audio player for audio file types. In some embodiments, a converter for converting from one file format to another file format may also be used to facilitate ease of use. For example, an audio file can be converted from a less supported file type to a more general file type or a file type supported by a client browser.

  Considering now FIG. 2, which illustrates an exemplary example of a predictive storage service in accordance with at least one embodiment using a file structure 206. The file structure 206 can be monitored for important files 212 that can be identified via monitoring information and file metadata. Other files 210 may be considered less important. For example, a predictive storage application on computing system 202 can monitor storage device 204 connected to computing system 202. In the illustrated embodiment, the storage device 204 includes a file structure 206 having a hierarchical nature. The folder 208 may include other folders 208 and / or files 210 and / or 212. The predictive storage application can register and / or scan the file structure 206 at any time to be notified of file events.

  For example, the predictive storage application can be installed on a computing system 202 that operates as a background service. The predictive storage application can monitor storage devices 204 such as hard drives to monitor information and file metadata as described above. The predictive storage application can determine the importance rating for a particular file based on importance indicators prepared from scan and / or file events. Using the importance rating, a series 214 of important files 212 is determined and sent to the predictive storage service. In one embodiment, an importance index score is given that starts at 5 points and decreases with 1 point being deducted after 24 hours. An editable file is given 2 points, while a document containing text is given 1 point. Files with an importance score of 6 points or higher are considered important and may not be sent to the predictive storage service with a score of 5 points or lower.

  In some embodiments, the file is encrypted. In one embodiment, the file is transmitted via TLS / SSL. In other embodiments, the file is encrypted prior to leaving computing system 202 for storage as an encrypted file. By encrypting the file, the predictive storage application can reduce the risk of interception and / or leakage of sensitive information.

  The predictive storage application may be configured by a user and / or administrator to include and / or exclude files, file types, folders, monitoring information and file metadata. In one embodiment, an administrator can configure a predictive storage application for a set of business computing systems. The critical file may be sent to the team member's computing system so that the team member can view at least the latest information determined to be relevant to the other team members.

  Considering now FIG. 3, which illustrates an exemplary example of a process 300 that may be used to synchronize files with a predictive storage service in accordance with at least one embodiment. Process 300 is accomplished by using one or more computing resources found in FIG. 1, such as desktop computer system 104, mobile device 106, file 102, predictive storage service 110, Internet 108 and server 112. Can do. The predictive storage application may be installed 302 on the computing system. The computing system can also register 304 with the predictive storage service. For example, as part of an installation, a software client can contact a predictive storage service and use it to identify that the client is associated with a customer account, such as a username and password or digital key Credentials can be provided. A software client may be given a set of credentials, such as a key used to identify the client, by the predictive storage service. In other embodiments, the MAC address, one or more identification information about the system, or a hash of other identification information can be registered with the predictive storage service and used to identify the client. Other systems can be added by installing the appropriate application for the operating system and registering the device with the predictive storage service. The predictive storage application (s) can monitor the file 308 for measurements and / or events that are determined to indicate the potential importance of the file. In some embodiments, events can be used to measure user interaction with a file. If a high importance file 310 is not found, and no new system needs to be registered, the file may continue to be monitored 308. If a potentially important file is detected 310, the importance of the file can be calculated 312. For example, if the predictive storage application receives an event in which a word processing file is stored, the predictive storage application can react and determine the rating of the importance of the file. If the rating indicates that the file is sufficiently important 314, the file is sent to the predictive storage service 316 and can be sent to other registered devices. The process may then repeat starting at block 308. However, if the file is not sufficiently important 314, the process may repeat starting at block 308. It should be noted that other devices may be added at various times, including after the fact.

  Some or all of process 300 (or any other process described herein, or variations and / or combinations thereof) may control one or more computer systems comprised of executable instructions. Code that may be executed in bulk on one or more processors (eg, executable instructions, one or more computer programs, or one, by hardware or a combination thereof) Or a plurality of applications). The code may be stored on a computer-readable storage medium, for example, in the form of a computer program comprising a plurality of instructions that can be executed by one or more processors. The computer readable storage medium may be non-transitory.

  It should be noted that although specific examples of processes are shown, some of the process operations may be performed in parallel instead of serially. For example, the operation of sending 316 a file to a service and sending it to a registered device can be performed in parallel. In another example, application installation 302 and computing system registration 304 can be performed in parallel on different computing systems.

  In another example, the first device may determine that the first file is important and the second device may determine that the second file is important. The first device may synchronize the first file with the predictive storage service and / or the second device. The second device can then synchronize the second file with the predictive storage service and / or the first device. As a result, the first file and the second file can be stored in the predictive storage service and / or both the first and second devices.

  The responsibility of the predictive storage application on the computing system is to determine which files should be usable outside of the computing system, such as on predictive storage services or other devices. FIG. 4 illustrates an exemplary example of a process 400 used to determine a file to select with a predictive storage service according to at least one embodiment. Process 400 may be accomplished by using one or more computational resources found in FIG. 1, such as desktop computer system 104, mobile device 106, file 102, predictive storage service 110, Internet 108, and server 112. it can. A predictive storage application resides on the computing system. The predictive storage application monitors the file structure 402 to indicate that the file should be shared outside the computing system. Using algorithms and / or heuristics based on monitoring and / or other information such as file metadata, the predictive storage application may selectively determine 404 which files to send to the predictive storage service. Can do. For example, the importance rating can be increased by attributes such as the file was recently opened, recently saved, or has a word processing extension. If the importance rating is high enough, the file can be selected to be sent to the predictive storage service. Once selected, the file can be uploaded to the predictive storage service 406. For example, the predictive storage application may make an application programming interface call to the predictive storage service using a secure communication channel such as TLS / SSL. In some embodiments, the file may be encrypted on the computing system by the predictive storage application before being sent to the predictive storage service.

  In one embodiment shown in FIG. 5, monitoring may include event-based monitoring. Process 500 may be accomplished by using one or more computational resources shown in FIG. 1, such as desktop computer system 104, mobile device 106, file 102, predictive storage service 110, Internet 108, and server 112. it can. The predictive storage application may receive 502 a file operation event notification that triggers a file importance determination associated with the file operation. Information about the file may be collected before a decision is made. In the illustrated embodiment, use of the file between other devices can be determined 504 by opening, saving, or deleting the file. The file type can be determined 506. In some embodiments, shared files such as word processing documents, spreadsheets, images and / or documents are not normally used files such as configuration files, backup files and / or executable files. A higher importance may be given. A history of events associated with the file can be determined 508. For example, if a file has multiple saves on the last day and has multiple opening events and / or active window durations that exceed a threshold, then the importance rating of the file can be increased. . It is also determined 510 to use the file in conjunction with other applications. For example, the importance rating of a file can be improved when the file is opened in conjunction with another important file. In another embodiment, changing the focus between a file with an already determined importance and a file under review can increase the importance rating of the file under review. Since this information collected in operations 504 to 510 is an example of potential information collection, other considerations can also be used. Using the collected information, the importance rating of the file can be determined 512. If it is determined to be sufficiently important 514, the file is sent to service 516 and the process is then repeated at operation 502. If the file does not have sufficient importance 514, the predictive storage application is returned and will wait for a new event in operation 502.

  In some embodiments, the importance rating can be tailored to the needs of the client. In one embodiment, the predictive storage system may be used with a user. The user can configure the document to include or exclude folders (such as system folders) and decide whether to include temporary volumes such as USB drives. Similarly, importance rating calculations can also be configured. For example, a photographer may be more interested in images than documents, while a patent attorney may be more interested in documents and technical drawings than images. The predictive storage application may include a default configuration.

  In another embodiment, the predictive storage system can be used with an administrator in an enterprise or team environment. Files uploaded to the predictive storage service can respect the file access rights given to the user of the file. For example, a file that is read-only to the team but that is determined to be important may remain in a read-only state. To convert a word processing document into a series of images, the file can optionally be converted to a format that complies with read-only conditions on the device receiving the document. In another embodiment, access permissions may be adhered to by a predictive storage service that only distributes files deemed important to team members who have the authority to view / edit documents.

  In some embodiments, the predictive storage service can facilitate file transfer between devices rather than acting as a repository of files. FIG. 6 illustrates an exemplary example of a process 600 that can be used to synchronize files with a predictive storage service according to at least one embodiment. Process 600 may be accomplished by using one or more computational resources shown in FIG. 1, such as desktop computer system 104, mobile device 106, file 102, predictive storage service 110, Internet 108, and server 112. it can. The predictive storage service can register 602 an account with the customer. The client can refer to the account and register 604 with the computing system. If more computing systems are available, the registration process can be performed multiple times on multiple devices, so they may also register. The predictive storage system can receive 606 files that are synchronized with other registered systems. In some embodiments, a file can be received from a predictive storage application running on a registered system. In one embodiment, the received file is encrypted. In another embodiment, the encryption key is known to the registration system but not to the predictive storage service.

  After receiving 606 the file, one or more registered devices or systems can synchronize 608 the file. In some embodiments, the predictive storage service may attempt to synchronize files until success is achieved. Other registered systems can also be synchronized. Once all systems are synchronized, the file can be removed 610 from service. In one embodiment, the predictive storage service does not actually store the file, but operates to synchronize with the device. For example, a first computing system can receive an address of a second computing system that synchronizes files. In this way, the predictive storage system serves as an address book for synchronization. In some embodiments, the registered computing system changes the network or is behind a firewall, so the predictive storage application on the computing system periodically updates the address of the contact. It becomes possible.

  In some embodiments, the predictive storage service may function as a repository of files that are searched by registered computing systems. FIG. 7 illustrates an exemplary example of a process 700 that may be used to store a file in a predictive storage service according to at least one embodiment. Process 700 may be accomplished by using one or more computational resources found in FIG. 1, such as desktop computer system 104, mobile device 106, file 102, predictive storage service 110, Internet 108, and server 112. . The predictive storage service can register 702 an account with a customer. The client can refer to the account and register 704 the computing system. If more computing systems are available, they may also register. The predictive storage system can receive 706 a file from a computing system registered for storage. The predictive storage service may select one or more registered computing systems with which to synchronize 708 the file, and may attempt to synchronize the file until successful, if necessary. In some embodiments, multiple devices can be synchronized in parallel. Until it is determined that the file is no longer important, the file can be stored 710 in a predictive file storage service.

  In some embodiments, the file may be deleted from the predictive storage service depending on the configuration of this embodiment. The LRU algorithm expunges the oldest accessed file based on storage quota, such as size, number of files, or other measure of storage. In other embodiments, registered devices can be queried for a rating of the importance of stored files. Files that fall below the importance threshold can be deleted from the predictive storage service. In one embodiment, the importance rating can be determined by being accessed by the predictive storage service and the time held.

  In some embodiments, the file can be removed from the synchronization device except for the originating device. For example, the synchronized file may be stored in a temporary folder. The original of the file may exist in the file structure of the computing system. Depending on the device requirements, the temporary folder can delete files in a different time and manner than the predictive storage service. In some embodiments, erasing the file from the temporary folder may be based on the importance rating and / or configuration of the predictive storage application running on the device. In other embodiments, erasure of files from the temporary folder can be controlled by the predictive storage service.

  In other embodiments, the predictive storage service provides other services. For example, the predictive storage service can provide a search service that indexes received files. On demand, the index can be consulted to search among stored files. In another embodiment, the predictive storage service may provide access to files, such as via download or web application. For example, a word processing web application can provide edit access to a file.

  In one embodiment, the predictive storage service may include important file versions. For example, a user can edit a file on a mobile device at midnight. The next morning, the user may regret changes made at midnight. In the drop-down box, the user can also select a previous version to synchronize with the computing system and receive this previous version. If the file is deleted, the previous version can be used to restore the file. In another embodiment, the version can be obtained via an application auto-save feature. For example, a user may work on a file for several hours. Autosave files such as difference files can be uploaded to the predictive storage service for use on other computing systems. When the user puts the computing system to sleep and then moves to the second computing system, the user will be given the last automatic even if the file was not technically saved by the application on the previous computing system. You can continue editing from Save. In one embodiment, the previous auto-save can be selected as the previous version. Depending on the computing system and autosave, the predictive storage service can use the original file and autosave file to present an accurate playback of the selected version.

  In some embodiments, the predictive storage service decides to update an existing file stored by the predictive storage service rather than creating a new copy of the existing file. The predictive storage service may use internal analysis of a file or may ask a client agent for file analysis. In one internal analysis embodiment, the predictive storage application of the local computing device has determined in advance that the file has a sufficient importance rating and uploads the file to the predictive storage service. The predictive storage application may then determine that the file needs to be analyzed compared to the version of the file stored by the predictive storage service. Utilizing the fact of understanding the file format, the predictive storage application analyzes the data in the file to determine whether the file is current, modified, or outdated. Can be interpreted. If so, the predictive storage application can prepare to update the files in the predictive storage service. Sending an update eliminates the need to send all the files, saving bandwidth.

  In the client agent embodiment, the predictive storage application on the local computing device determines that the file has a sufficient importance rating and uploads the file in advance to the predictive storage service with a unique identifier from the client agent. ing. The predictive storage application may then determine that the file needs to be analyzed compared to the version of the file stored by the predictive storage service. This determination may be based on periodic scans or events such as local save events or file upload events at the predictive storage service. The predictive storage application can receive a unique identifier from a client agent performing file analysis. The unique identifier can be sent to the predictive storage service to allow the predictive storage service to determine whether the file is a new version, a current version, or an old version of the file. is there. If so, the predictive storage application can upload the file to the predictive storage service. If it is an older version, the predictive storage service can request the current version of the file.

  The updated version of the file can be saved by a predictive file service. In some embodiments, updated versions of files are stored in a tree structure with other versions and / or branching versions. In other embodiments, the new version overwrites the old version. The version of the file can also include unique identifier metadata. The unique identifier metadata may provide information about whether the version of the file is old, new or up to date compared to the version stored by the predictive file service. For example, the unique identifier may include an automatically incremented value, a time stamp, and a change creator identifier. In this embodiment, the latest version may be determined by the auto increment value. If the unique identifiers are the same, the file can be considered the latest. However, even if the auto-increment values are the same, there may be conflicting edits if the other fields do not match.

  FIG. 8 illustrates aspects of a data center environment 800 that can be used to support predictive storage services and / or streaming desktop services. Data center 800 may include a collection of shared computing resources and / or shared infrastructure. For example, as shown in FIG. 5, the data center 800 includes a virtual machine slot 804, a physical host 802, a power source 806, a router 808, a separation area 810, and a geographical location 812. The physical host 802 may be shared by multiple virtual machine slots 804, and each slot 804 can be used to host a virtual machine that includes a guest operating system. A plurality of physical hosts 804 can share a power source 806 like a power source 806 provided in a server rack. The router 808 can provide multiple physical hosts 804 to route network traffic across several power supplies 806. The isolated area 810 can provide a number of routers 808, and the isolated area 810 is a group of computing resources provided by redundancy, such as a backup generator. A plurality of isolated areas 810 may exist at a geographical location 812 such as the data center 800. One or more provisioning servers 814 may include a memory and processor configured with instructions for analyzing user data and utilized using a determined role and / or shared resource / computing infrastructure. Possible implementation resources can be rated. The provisioning server 814 can also manage the workflow for provisioning and deprovisioning of computing resources while simultaneously detecting the health status and / or failure of the computing resources.

  In one embodiment, the streaming desktop can be instantiated as a virtual machine in an available slot 804. As part of the provisioning process, slot 804 may also be linked to a predictive storage service and / or a predictive storage service account. Make files stored in the predictive storage service available to streaming desktop services in addition to or instead of other storage services such as block storage, object storage, and / or other high or low latency data stores Can do. The operating system display output may be routed to an external computing system via physical host 804 and router 808. Input can be routed to the host 802, routed inside the virtual machine, and provided to the operating system.

Embodiments of the present invention can be described in view of the following clauses.
1. A computer-implemented method for providing data, comprising:
Under the control of one or more computer systems comprised of executable instructions,
A virtual machine containing an operating system in a multi-tenant environment for service provider customers is run by the service provider,
Monitors the operating system for access to data files within the operating system file structure
Determine importance indicators for at least some of the data files in the file structure, each importance indicator being based at least in part on recent access to the respective data file in the file structure and uploaded Upload at least a portion of the data file from the file structure to the storage service based at least in part on the importance indicator so that the data file is cached on the server for distribution to other computing devices A method consisting of:
2. The computer-implemented method of clause 1, wherein the importance index is based at least in part on a Bloom filter.
3. The computer-implemented method of clause 1, further comprising making multiple versions of the uploaded data file available on the second computing system.
4). Further, to remove one or more of the uploaded data files on the server based at least in part on the second determination of the one or more importance indicators of the uploaded data files. The computer-implemented method according to clause 1, further comprising:
5. The computer-implemented method of clause 1, further comprising prompting the supplemental data file to support the uploaded data file with the uploaded data file to be cached on the server.
6). In addition, monitor the virtual machine for one or more changes to the uploaded data file,
The method of clause 1, comprising uploading one or more of the changes from the first computing system to the data file to form a new version of the data file.
7). A computer-implemented method for data storage comprising:
Under the control of one or more computer systems comprised of executable instructions,
Monitor the data file of the first computing system;
Determine the importance of one or more data files based at least in part on a quantified data inference algorithm;
Selectively determine a set of data files from one or more data files to be sent to the storage service based at least in part on the determined importance of the set of data files; and on other computing devices An execution method consisting of having a series of data files uploaded for the availability of a series of data files.
8). The computer-implemented method of clause 7, wherein determining the importance of the one or more data files includes calculating an importance rating based at least in part on the metadata describing the data file. Method.
9. The computer-implemented method according to clause 8, wherein the metadata includes a document type, a document access history, a document editing history, a keyword, or creator information.
10. Further, determining the importance of the one or more data files calculates an importance rating based at least in part on the relationship with the one or more applications installed on the first computing system. The computer-implemented method of clause 7 including the above.
11. 8. The computer-implemented method of clause 7, wherein the quantitative data inference algorithm is based at least in part on user interaction with one data file from one or more data files.
12 The clause 7, further comprising receiving an address of a second computing device registered with a storage service account to enable transmission of a series of data files to the second computing device. Computer execution method.
13. The computer-implemented method of clause 7, further comprising causing the series of data files to be stored by the storage service.
14 The computer-implemented method of clause 13, further comprising indexing the series of data files to allow retrieval of the series of data files.
15. Allowing the series of data files to be uploaded further includes clause 13 to encrypt the series of data files such that the series of data files are stored in an encrypted form in the storage service. The computer execution method as described.
16. The computer-implemented method of clause 7, further comprising determining an importance rating of the at least one file from the series of data files based at least in part on the file event or file attribute.
17. A computer system for data storage,
When executed by one or more processors, at least one or more processors,
A first computing system application configured to selectively determine a set of data files in a data structure to send to the storage service based on the determined importance of the data files;
An application of a second computing system configured to receive a data file from a storage service, and managing synchronization of the data file between the first computing system and the second computing system; A storage service configured with
A computer system comprised of one or more computing resources having one or more processors and memory that contain executable instructions to execute.
18. The computer system according to clause 17, wherein the second computing system is a mobile phone.
19. The computer system according to clause 17, wherein the first computing system further comprises a volume that accommodates the file structure, and wherein the data structure is a file structure.
20. The computer system of clause 17, wherein the storage service further comprises a storage device for storing a series of data files.
21. The computer system of clause 20, wherein the storage service further includes a web application that provides an editor for at least one data file from the series of data files stored by the storage device.
22. 21. The computer system of clause 20, further comprising a search service that indexes a series of files stored in a storage device and provides a search interface.
23. When executed by one or more processors, the computer system at least
Determine the importance of the data file of the first computing system;
Based at least in part on the determined importance of the series of data files, the series of data files to be sent to the storage service is selectively determined from the first computing system, and the first computing system and the first computing file Associating two computing systems and uploading a series of data files to a system configured to send the uploaded files to a second computing system;
One or more computer-readable storage media that collectively store executable instructions.
24. The instructions further include instructions that, when executed, cause the computer system to store the series of files at least temporarily, and uploading the series of data files distributes the series of data files to the second computing system. The computer-readable storage medium according to clause 23, comprising:
25. The instructions further comprise instructions that, when executed, cause the computer system to at least limit the series of files to a series of file subsets based at least in part on the access rights granted to the user of the second computing system. 26. The computer-readable storage medium according to clause 23, comprising: 24. The computer readable storage medium of clause 23, wherein the determined importance is based at least in part on a recency of access to each data file in the series of data files.
27. 24. The computer readable storage medium of clause 23, wherein the determined importance is based at least in part on a set of applications installed on the first computing system.
28. A series of said data files is a list of data files determined to be sent to a second computing system; and
Uploading the series of data files includes receiving an address of the second computing system to facilitate direct communication of the series of files to the second computing system by the first computing system. 24. The computer readable storage medium according to clause 23, comprising:
29. 24. The computer readable storage medium of clause 23, wherein the series of data files includes a subset of the series of data files in the folder along with at least one file from the series of data files in the folder that is outside the subset.

  FIG. 9 illustrates aspects of an example environment 900 for implementing aspects in accordance with various embodiments. As will be appreciated, a web-based environment is used for illustrative purposes, but different environments can be used as appropriate to implement various embodiments. The environment includes an electronic client device 902, which is operable to send and receive requests, messages or information via an appropriate network 904 and be operable to communicate the information back to the user of the device. Devices may be included. Examples of such client devices include personal computers, cell phones, handheld messaging devices, laptop computers, set-top boxes, personal data assistants, electronic book readers, and the like. The network may include any suitable network including an intranet, the Internet, a cellular network, a local area network, or any other such network or combination thereof. The components used in such a system can depend at least in part on the type of network and / or environment selected. Protocols and components for communicating over such networks are well known and will not be discussed in detail herein. Communication over the network can be enabled with a wired or wireless connection, or a combination thereof. In this embodiment, as would be apparent to one skilled in the art, alternative devices that serve similar purposes can be used for other networks, but for receiving content and providing content in response thereto. Since the environment includes a Web server 906, the network includes the Internet.

  An exemplary environment includes at least one application server 908 and a data store 910. There are a number of application servers, layers, or other elements, processes or components that are chained or otherwise configured to interact to perform tasks such as retrieving data from the appropriate data store It should be understood that it is possible to do. As used herein, the term “data store” refers to any device or combination of devices that can store, access, and retrieve data, including data servers, databases, data storage devices, and any standard. Any combination and any number of data storage media in a distributed or clustered environment. An application server is optional for integrating with a data store as needed to perform one or more aspects of the application for data access for the application, client devices that handle most of the business logic. Appropriate hardware and software can be included. The application server can collaborate with the data store to provide access control services and generate content such as text, graphics, audio and / or video that is transferred to the user, in this example they are It can be provided to the user by the web server in the form of a hypertext markup language (“HTML”), an extended markup language (“XML”), or another suitable structured language. All requests and responses, as well as content distribution operations between the client device 902 and the application server 908, can be processed by the web server. The structured code described herein can be executed on any suitable device or host machine, as described elsewhere, so no web and application servers are required, It should be understood that these are merely exemplary components.

  Data store 910 may include a number of separate data tables, databases or other data storage mechanisms and media for storing data related to a particular aspect. For example, the illustrated data store includes a mechanism for storing production data 912 and user information 916, which can be used to provide content to the production side. The data store is also shown to include a mechanism for storing log data 914 and can be used for reporting, analysis, or other such purposes. For example, there may be many other aspects that may need to be stored in the data store for page image information and to access the appropriate information, and these are any of the mechanisms listed above. It should be understood that the data store 910 can be stored as a suitable or additional mechanism. The data store 910 is operable via logic associated therewith to receive instructions from the application server 908, in response to obtaining, updating, or otherwise processing data. In one embodiment, the user may send a search request for a certain type of item. In this case, the data store may access user information to verify the user's identity, and may access catalog detail information to obtain information about that type of item. The information can then be returned to the user, for example, in a results list on a web page that the user can view on the user device 902 via a browser. Information about a particular item of interest can be viewed by opening a dedicated page or browser window.

  Each server typically includes an operating system that provides executable program instructions for the overall management and operation of the server, and when executed by the server's processor, is intended for the server. A computer-readable storage medium (eg, hard disk, random access memory, read-only memory, etc.) that stores instructions that cause a particular function to be executed will typically be included. Appropriate implementations for server operating systems and general functionality are known or commercially available, particularly easily implemented by those having ordinary skill in the art, especially in light of the disclosure herein. ing.

  The environment in one embodiment is a distributed computing environment that utilizes several computer systems and components that are connected to each other via a communication link using one or more computer networks or direct connections. However, it will be appreciated by those skilled in the art that such a system can work equally well with a system having fewer or more components than that shown in FIG. Therefore, the illustration of system 900 in FIG. 9 should be construed as illustrative in nature and not as limiting the scope of the invention.

  Various embodiments can also be implemented in a wide variety of operating environments, and in some cases, one or more users that can be used to operate any of a number of applications. A computer, computing device or processing unit may be included. Users or client devices can be a number of general purpose personal computers, such as desktop or laptop computers running standard operating systems, as well as mobile phones, mobile phones that can run mobile software to support a number of networking and messaging protocols. It can include either wireless or portable devices. Such a system can also include a number of workstations running any of a variety of commercially available operating systems and other known applications for purposes such as development and database management. These devices can include other electronic devices such as dummy terminals, thin clients, game systems and other devices that can communicate over a network.

  Most embodiments include: Transmission Control Protocol / Internet Protocol (“TCP / IP”), Open System Interconnection (“OSI”), File Transfer Protocol (“FTP”), Universal Plug and Play (“UpnP”), Network Well known to those skilled in the art to support communications using any of a variety of commercially available protocols such as File System (“NFS”), Common Internet File System (“CIFS”), and AppleTalk. Utilize at least one network that would be known. The network can be, for example, a local area network, a wide area network, a virtual private network, the Internet, an intranet, an extranet, a public switched telephone network, an infrared network, a wireless network, and any combination thereof.

  In embodiments utilizing a Web server, the Web server may be a hypertext transfer protocol (“HTTP”) server, an FTP server, a common gateway interface (CGI) server, a data server, a Java server, and a business. Any of a wide variety of server or mid-tier applications including application servers can be executed. These server (s) can execute a program or script in response to a request from a user device by executing one or more Web applications. Trademark), C, C # or C ++, or Perl, Python or TCL, and combinations thereof, etc., can be implemented as one or more scripts or programs written in any programming language. Similarly, the server (s) may comprise a database server including those commercially available from Oracle®, Microsoft®, Sybase®, and IBM®. Although it is, it is not limited to these.

  As described above, the environment can include a variety of data stores and other memories and storage media. These may reside in various locations, such as on a local storage medium (and / or provided internally) to one or more computers or remote from any or all of the computers over a network. . In certain embodiments, the information may reside in a storage area network (“SAN”) that is well known to those skilled in the art. Similarly, any necessary files for performing functions attributable to a computer, server or other network device may be stored locally and / or remotely as desired. Where the system includes computerized devices, each such device can be, for example, at least one central processing unit (“CPU”), at least one input device (eg, mouse, keyboard, controller, touch screen or keypad). ), And hardware elements that can be electrically coupled via a bus to elements including at least one output device (eg, display device, printer or speaker). Similarly, such systems also include one or more storage such as disk drives, optical storage devices, and solid state storage devices such as random access memory (“RAM”) or read only memory (“ROM”). The device may include a removable media device such as a memory card, flash card, or the like.

  Such a device may comprise a computer readable storage medium reader, a communication device (eg, a modem, a network card (wireless or wired), an infrared communication device, etc.) and a working memory as described above. A computer readable storage medium reader is a computer readable storage medium that means a remote, local, fixed and / or removable storage device, as well as temporarily and / or more permanently computer readable information. It can be connected to storage media for receiving, storing, transmitting and retrieving, or can be configured to receive these media. Also, the system and various devices typically include a number of software applications, modules, services or other elements located within at least one working memory device that includes an operating system and application programs such as client applications and web browsers. Will be included. It should be understood that alternative embodiments may have numerous variations from those described above. For example, customized hardware may be used and / or certain elements may be implemented in hardware, software (eg, including portable software such as applets), or both. In addition, connections to other computing devices such as network input / output devices can be used.

  Storage media and computer readable media for containing code or portions of code may include RAM, ROM, electrically erasable programmable read only memory (“EEPROM”), flash or other memory technology, compact disk read only memory ( "CD-ROM"), digital versatile disk (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage, or may be used to store desired information Any method or technique for storage and / or transmission of information such as computer readable instructions, data structures, program modules or other data, including any other medium that can be accessed by the devices of the system Implemented, volatile and non-volatile, It will include any suitable medium known and used in the art, including but not limited to storage media and communication media such as removable and non-removable. Based on the disclosure and teachings provided herein, a person of ordinary skill in the art will recognize other means and / or methods for implementing various embodiments.

  The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense. However, it will be apparent that various modifications and changes can be made without departing from the broader spirit and scope of the invention as set forth in the claims.

  Other variations are within the scope of the present invention. Thus, while the disclosed technology is susceptible to various modifications and alternative constructions, the specific embodiments illustrated are shown in the drawings and have been described above in detail. However, it is not intended to limit the invention to the particular form or form disclosed, but on the contrary, the intention is within the spirit and scope of the invention as defined in the appended claims. It should be understood that all modifications, alternative constructions and equivalents that come in are included.

  The use of the terms “a” and “an” and “the” in the context of describing the disclosed embodiments (particularly in the context of the following claims), and similar indicators, are specifically described herein. It should be interpreted as covering both the singular and the plural unless explicitly stated otherwise or inconsistent with the context. The terms “comprising”, “having”, “including” and “accommodating” are to be interpreted as unrestricted terms (ie, including but not limited to) unless otherwise specified. It is. The term “connected” is to be interpreted as being partly or completely contained within, attached to, or connected together, even with the presence of something to be joined. Should. The recitation of value ranges herein is merely intended to serve as a shorthand notation for individually referring to each distinct value falling within the range, unless otherwise indicated herein. The values of are those incorporated herein as if they were individually described herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language herein (eg, “like”) is intended only to better elucidate embodiments of the present invention, and is claimed separately. Unless otherwise, the scope of the present invention is not limited. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.

  Preferred embodiments of this disclosure are described herein, including the best mode known to the inventors for carrying out the invention. Variations of these preferred embodiments will become apparent to those skilled in the art upon reading the foregoing description. We expect that those skilled in the art will adopt such modifications as appropriate, and that we will implement the invention in a manner other than that specifically described herein. Intended. Accordingly, this invention includes all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. Also, any combination of the above-described elements in all possible variations thereof is encompassed by the invention unless otherwise indicated herein or otherwise clearly contradicted by context.

  All references cited in this specification, including publications, patent applications and patents, are indicated as if each reference were individually and specifically to be incorporated herein by reference and as if fully set forth herein. Are incorporated herein by reference to the same extent.

Claims (15)

A computer-implemented method for a data storage device, comprising:
Under the control of one or more computer systems comprised of executable instructions,
Monitoring a data file of the first computing system;
Determining the importance of one or more data files based at least in part on a quantified data inference algorithm;
Selectively determining to send the set of data files from the one or more data files to a storage service based at least in part on the determined importance of the set of data files; Uploading the set of data files for availability of the set of data files on a storage device.   The method of claim 1, wherein determining the importance of one or more data files further comprises calculating an importance rating based at least in part on metadata describing the data file. The computer execution method as described.   The computer-implemented method according to claim 2, wherein the metadata includes a document type, a document access history, a document editing history, a keyword, or creator information.   The step of determining the importance of the one or more data files calculates an importance rating based at least in part on the relationship with the one or more applications installed on the first computing system. The computer-implemented method of claim 1, further comprising a step.   The computer-implemented method of claim 1, wherein the quantified data inference algorithm is based at least in part on a user interface with a data file from one or more of the data files.   Further comprising receiving an address of a second computing device registered with the storage service account to enable transmission of the set of data files to the second computing device. The computer-implemented method according to claim 1, wherein:   The computer-implemented method of claim 1, further comprising the step of storing the set of data files by the storage service.   The computer-implemented method of claim 1, further comprising the step of indexing the set of data files to enable retrieval of the set of data files.   The step of uploading the set of data files includes the step of encrypting the set of data files such that the set of data files is stored in an encrypted form in the storage service. The computer-implemented method according to claim 1.   The computer-implemented method of claim 1, further comprising determining an importance rating of at least one file from the set of data files based at least in part on file events or file attributes. . A computer system for data storage,
When executed by one or more processors, at least one of the processors is
A first computing system application configured to selectively determine a set of data files in a data structure to send to the storage service based on the determined importance of the data files;
An application of a second computing system configured to receive the data file from the storage service;
One or more comprising executable instructions for executing the storage service configured to manage synchronization of the data file between the first computing system and the second computing system A computer system comprising one or more computing resources having a plurality of processors and memory.   The computer system according to claim 11, wherein the first computing system further includes a volume for storing a file structure, and the data structure is a file structure.   12. The computer system according to claim 11, wherein the storage service further comprises a storage device for storing the set of data files.   The computer system of claim 13, wherein the storage service further includes a web application that provides an editor for at least one data file from the set of data files stored by the storage.   14. The computer system of claim 13, further comprising a search service that indexes the set of files stored by the storage and provides a search interface.